## ----style, echo=FALSE, results="asis", message=FALSE-------------------- BiocStyle::markdown() knitr::opts_chunk$set(tidy = FALSE, warning = FALSE, message = FALSE) ## ----echo=FALSE, results='hide', message=FALSE--------------------------- library(DOSE) library(GO.db) library(org.Hs.eg.db) library(topGO) library(GSEABase) library(clusterProfiler) ## ------------------------------------------------------------------------ x <- c("GPX3", "GLRX", "LBP", "CRYAB", "DEFB1", "HCLS1", "SOD2", "HSPA2", "ORM1", "IGFBP1", "PTHLH", "GPC3", "IGFBP3","TOB1", "MITF", "NDRG1", "NR1H4", "FGFR3", "PVR", "IL6", "PTPRM", "ERBB2", "NID2", "LAMB1", "COMP", "PLS3", "MCAM", "SPP1", "LAMC1", "COL4A2", "COL4A1", "MYOC", "ANXA4", "TFPI2", "CST6", "SLPI", "TIMP2", "CPM", "GGT1", "NNMT", "MAL", "EEF1A2", "HGD", "TCN2", "CDA", "PCCA", "CRYM", "PDXK", "STC1", "WARS", "HMOX1", "FXYD2", "RBP4", "SLC6A12", "KDELR3", "ITM2B") eg = bitr(x, fromType="SYMBOL", toType="ENTREZID", OrgDb="org.Hs.eg.db") head(eg) ## ------------------------------------------------------------------------ library(org.Hs.eg.db) keytypes(org.Hs.eg.db) ## ------------------------------------------------------------------------ ids <- bitr(x, fromType="SYMBOL", toType=c("UNIPROT", "ENSEMBL"), OrgDb="org.Hs.eg.db") head(ids) ## ------------------------------------------------------------------------ data(gcSample) hg <- gcSample[[1]] head(hg) eg2np <- bitr_kegg(hg, fromType='kegg', toType='ncbi-proteinid', organism='hsa') head(eg2np) ## ----eval=FALSE---------------------------------------------------------- ## bitr_kegg("Z5100", fromType="kegg", toType='ncbi-geneid', organism='ece') ## ------------------------------------------------------------------------ bitr_kegg("Z5100", fromType="kegg", toType='ncbi-proteinid', organism='ece') bitr_kegg("Z5100", fromType="kegg", toType='uniprot', organism='ece') ## ----warning=FALSE------------------------------------------------------- data(geneList, package="DOSE") gene <- names(geneList)[abs(geneList) > 2] gene.df <- bitr(gene, fromType = "ENTREZID", toType = c("ENSEMBL", "SYMBOL"), OrgDb = org.Hs.eg.db) head(gene.df) ggo <- groupGO(gene = gene, OrgDb = org.Hs.eg.db, ont = "CC", level = 3, readable = TRUE) head(ggo) ## ------------------------------------------------------------------------ ego <- enrichGO(gene = gene, universe = names(geneList), OrgDb = org.Hs.eg.db, ont = "CC", pAdjustMethod = "BH", pvalueCutoff = 0.01, qvalueCutoff = 0.05, readable = TRUE) head(ego) ## ----eval=FALSE---------------------------------------------------------- ## ego2 <- enrichGO(gene = gene.df$ENSEMBL, ## OrgDb = org.Hs.eg.db, ## keytype = 'ENSEMBL', ## ont = "CC", ## pAdjustMethod = "BH", ## pvalueCutoff = 0.01, ## qvalueCutoff = 0.05) ## ----eval=FALSE---------------------------------------------------------- ## ego2 <- setReadable(ego2, OrgDb = org.Hs.eg.db) ## ----eval=FALSE---------------------------------------------------------- ## ego3 <- gseGO(geneList = geneList, ## OrgDb = org.Hs.eg.db, ## ont = "CC", ## nPerm = 1000, ## minGSSize = 100, ## maxGSSize = 500, ## pvalueCutoff = 0.05, ## verbose = FALSE) ## ------------------------------------------------------------------------ search_kegg_organism('ece', by='kegg_code') ecoli <- search_kegg_organism('Escherichia coli', by='scientific_name') dim(ecoli) head(ecoli) ## ------------------------------------------------------------------------ kk <- enrichKEGG(gene = gene, organism = 'hsa', pvalueCutoff = 0.05) head(kk) ## ------------------------------------------------------------------------ kk2 <- gseKEGG(geneList = geneList, organism = 'hsa', nPerm = 1000, minGSSize = 120, pvalueCutoff = 0.05, verbose = FALSE) head(kk2) ## ----eval = FALSE-------------------------------------------------------- ## mkk <- enrichMKEGG(gene = gene, ## organism = 'hsa') ## ----eval=FALSE---------------------------------------------------------- ## mkk2 <- gseMKEGG(geneList = geneList, ## species = 'hsa') ## ----eval=FALSE---------------------------------------------------------- ## david <- enrichDAVID(gene = gene, ## idType = "ENTREZ_GENE_ID", ## listType = "Gene", ## annotation = "KEGG_PATHWAY", ## david.user = "clusterProfiler@hku.hk") ## ------------------------------------------------------------------------ gmtfile <- system.file("extdata", "c5.cc.v5.0.entrez.gmt", package="clusterProfiler") c5 <- read.gmt(gmtfile) egmt <- enricher(gene, TERM2GENE=c5) head(egmt) egmt2 <- GSEA(geneList, TERM2GENE=c5, verbose=FALSE) head(egmt2) ## ----fig.height=5, fig.width=9------------------------------------------- barplot(ggo, drop=TRUE, showCategory=12) ## ----fig.height=5, fig.width=8------------------------------------------- barplot(ego, showCategory=8) ## ------------------------------------------------------------------------ dotplot(ego) ## ----fig.cap="enrichment map of enrichment result", fig.align="center", fig.height=16, fig.width=16, eval=FALSE---- ## enrichMap(ego) ## ----fig.height=14, fig.width=14, eval=FALSE----------------------------- ## ## categorySize can be scaled by 'pvalue' or 'geneNum' ## cnetplot(ego, categorySize="pvalue", foldChange=geneList) ## ----fig.height=12, fig.width=8------------------------------------------ plotGOgraph(ego) ## ----fig.cap="plotting gsea result", fig.align="center", fig.height=6, fig.width=8---- gseaplot(kk2, geneSetID = "hsa04145") ## ----eval=FALSE---------------------------------------------------------- ## browseKEGG(kk, 'hsa04110') ## ----eval=FALSE---------------------------------------------------------- ## library("pathview") ## hsa04110 <- pathview(gene.data = geneList, ## pathway.id = "hsa04110", ## species = "hsa", ## limit = list(gene=max(abs(geneList)), cpd=1)) ## ------------------------------------------------------------------------ data(gcSample) lapply(gcSample, head) ## ------------------------------------------------------------------------ ck <- compareCluster(geneCluster = gcSample, fun = "enrichKEGG") head(as.data.frame(ck)) ## ------------------------------------------------------------------------ mydf <- data.frame(Entrez=names(geneList), FC=geneList) mydf <- mydf[abs(mydf$FC) > 1,] mydf$group <- "upregulated" mydf$group[mydf$FC < 0] <- "downregulated" mydf$othergroup <- "A" mydf$othergroup[abs(mydf$FC) > 2] <- "B" formula_res <- compareCluster(Entrez~group+othergroup, data=mydf, fun="enrichKEGG") head(as.data.frame(formula_res)) ## ----fig.height=7, fig.width=9------------------------------------------- dotplot(ck) ## ----fig.height=6, fig.width=10------------------------------------------ dotplot(formula_res) dotplot(formula_res, x=~group) + ggplot2::facet_grid(~othergroup) ## ----echo=FALSE---------------------------------------------------------- sessionInfo()